Personality, social support, and loneliness among centenarians: a comparison between self- and proxy reports

Personality and social provisions as important personal and environmental resources have important effects on loneliness. The purpose of this study was to compare self- and proxy reports about centenarians concerning the relationship among personality, social support and loneliness. The mediating and moderating effects of social provisions between personality and loneliness were also examined. The sample included 124 centenarians and their proxies in the Georgia Centenarian Study. Demographic variables, education, subjective health, depression, Extraversion, Neuroticism and social provisions were included as measurements. Paired t-tests, bivariate correlations, multiple regression analyses and path models were computed. Results indicated that proxies reported significantly higher scores on social provisions and loneliness than centenarians themselves. The structural models for self- and proxy reports were quite similar. Neuroticism and social provisions predicted loneliness in both centenarian self- and proxy reports. Extraversion affected loneliness indirectly through social provisions in both self- and proxy report models. No moderating effects of social provisions were found in self- or proxy reports. There are commonalities between centenarian self- and proxy reports but there are also important differences that suggest unique variance to each perspective. Results indicate that proxy reports should be viewed as supplemental information for researcher and practitioners. Knowing the differences of centenarian self- and proxy reports could help caregivers realize the difference in perspective and help them learn about the centenarians\u27 loneliness better and thus provide improved quality of care and help

One-Shot Fine-Grained Instance Retrieval

Fine-Grained Visual Categorization (FGVC) has achieved significant progress recently. However, the number of fine-grained species could be huge and dynamically increasing in real scenarios, making it difficult to recognize unseen objects under the current FGVC framework. This raises an open issue to perform large-scale fine-grained identification without a complete training set. Aiming to conquer this issue, we propose a retrieval task named One-Shot Fine-Grained Instance Retrieval (OSFGIR). "One-Shot" denotes the ability of identifying unseen objects through a fine-grained retrieval task assisted with an incomplete auxiliary training set. This paper first presents the detailed description to OSFGIR task and our collected OSFGIR-378K dataset. Next, we propose the Convolutional and Normalization Networks (CN-Nets) learned on the auxiliary dataset to generate a concise and discriminative representation. Finally, we present a coarse-to-fine retrieval framework consisting of three components, i.e., coarse retrieval, fine-grained retrieval, and query expansion, respectively. The framework progressively retrieves images with similar semantics, and performs fine-grained identification. Experiments show our OSFGIR framework achieves significantly better accuracy and efficiency than existing FGVC and image retrieval methods, thus could be a better solution for large-scale fine-grained object identification.Comment: Accepted by MM2017, 9 pages, 7 figure

FfDL : A Flexible Multi-tenant Deep Learning Platform

Deep learning (DL) is becoming increasingly popular in several application domains and has made several new application features involving computer vision, speech recognition and synthesis, self-driving automobiles, drug design, etc. feasible and accurate. As a result, large scale on-premise and cloud-hosted deep learning platforms have become essential infrastructure in many organizations. These systems accept, schedule, manage and execute DL training jobs at scale. This paper describes the design, implementation and our experiences with FfDL, a DL platform used at IBM. We describe how our design balances dependability with scalability, elasticity, flexibility and efficiency. We examine FfDL qualitatively through a retrospective look at the lessons learned from building, operating, and supporting FfDL; and quantitatively through a detailed empirical evaluation of FfDL, including the overheads introduced by the platform for various deep learning models, the load and performance observed in a real case study using FfDL within our organization, the frequency of various faults observed including unanticipated faults, and experiments demonstrating the benefits of various scheduling policies. FfDL has been open-sourced.Comment: MIDDLEWARE 201

Cervical HPV infection in Yueyang, China: a cross-sectional study of 125,604 women from 2019 to 2022

ObjectiveHuman papillomavirus (HPV) infection is currently the main cause of cervical cancer and precancerous lesions in women. The aim of this study was to investigate the epidemiological characteristics of HPV genotypes among women in Yueyang city and to provide a basis for the prevention and treatment of cervical cancer in this city.MethodsA cross-sectional study was conducted on 125,604 women who had received treatment from eight hospitals in Yueyang city from September 2019 to September 2022. Analysis of the prevalence of HPV in patients.ResultsThe prevalence of HPV was 20.5% (95%CI: 20.2–20.7%), of which the high-risk type (HR-HPV) accounted for 17.5% (95%CI: 17.3–17.7%) and the low-risk type (LR-HPV) accounted for 5.0% (95%CI: 4.9–5.1%). Among the HR-HPV subtypes, the top five in prevalence, from the highest to the lowest, were HPV52 (5.1%), HPV16(2.7%), HPV58 (2.6%), HPV53 (2.4%), and HPV51 (1.7%). The main LR-HPV infection types were HPV81 (2,676 cases, OR = 2.1%; 95%CI, 2.0–2.1%). Among the infected patients, 19,203 cases (OR = 74.3%; 95%CI, 73.8–74.9%) had a single subtype, 4,673 cases (OR = 18.1%; 95%CI, 17.6–18.6%) had two subtypes, and 1957 cases (OR = 7.6%; 95%CI, 7.3–7.9%) had three or more subtypes. HPV prevalence is highest among women <25 years, 55–64 years and ≥ 65 years of age.ConclusionThe prevalence of HPV in women in Yueyang city was 20.5%, with HR-HPV being dominant. As women aged <25 years, 55–64 years, and ≥ 65 years are at a relatively higher risk, more attention should be paid to them for prevention and control of HPV infections

Open-source genomic analysis of Shiga-toxin–producing E. coli O104:H4

An outbreak caused by Shiga-toxin–producing Escherichia coli O104:H4 occurred in Germany in May and June of 2011, with more than 3000 persons infected. Here, we report a cluster of cases associated with a single family and describe an open-source genomic analysis of an isolate from one member of the family. This analysis involved the use of rapid, bench-top DNA sequencing technology, open-source data release, and prompt crowd-sourced analyses. In less than a week, these studies revealed that the outbreak strain belonged to an enteroaggregative E. coli lineage that had acquired genes for Shiga toxin 2 and for antibiotic resistance